James Ting-Ho Lo

43 papers B 6Misc 6Journal 22Unranked 9
YearRankTypeTitle / Venue / Authors
2020 J jnl
Adaptively Solving the Local-Minimum Problem for Deep Neural Networks.
CoRR
Huachuan Wang, James Ting-Ho Lo
2020 J jnl
Low-Order Model of Biological Neural Networks.
CoRR
Huachuan Wang, James Ting-Ho Lo
2018 J jnl
Chaotic synchronization based on neural filter.
J. Frankl. Inst.
Yu Guo, Fei Wang, James Ting-Ho Lo
2017 Misc conf
A neural filter-based scheme for synchronizing chaotic systems.
ICASSP
Yu Guo, Fei Wang, James Ting-Ho Lo
2017 — conf
Nonlinear system identification based on recurrent neural networks with shared and specialized memories.
ASCC
Yu Guo, Fei Wang, James Ting-Ho Lo
2017 — conf
Solving the Local-Minimum Problem in Training Deep Learning Machines.
ICONIP (1)
James Ting-Ho Lo, Yichuan Gui, Yun Peng
2016 B conf
Accommodative neural filters.
IJCNN
James Ting-Ho Lo, Yu Guo
2016 B conf
Training deep neural networks with gradual deconvexification.
IJCNN
James Ting-Ho Lo, Yichuan Gui, Yun Peng
2015 J jnl
The normalized risk-averting error criterion for avoiding nonglobal local minima in training neural networks.
Neurocomputing
James Ting-Ho Lo, Yichuan Gui, Yun Peng
2014 B conf
A pairwise algorithm for training multilayer perceptrons with the normalized risk-averting error criterion.
IJCNN
Yichuan Gui, James Ting-Ho Lo, Yun Peng
2013 — conf
Overcoming the Local-Minimum Problem in Training Multilayer Perceptrons with the NRAE-MSE Training Method.
ISNN (1)
James Ting-Ho Lo, Yichuan Gui, Yun Peng
2013 B conf
Overcoming the local-minimum problem in training multilayer perceptrons by gradual deconvexification.
IJCNN
James Ting-Ho Lo, Yichuan Gui, Yun Peng
2012 J jnl
A cortex-like learning machine for temporal hierarchical pattern clustering, detection, and recognition.
Neurocomputing
James Ting-Ho Lo
2012 — conf
Overcoming the Local-Minimum Problem in Training Multilayer Perceptrons with the NRAE Training Method.
ISNN (1)
James Ting-Ho Lo, Yichuan Gui, Yun Peng
2011 J jnl
A Low-Order Model of Biological Neural Networks.
Neural Comput.
James Ting-Ho Lo
2011 B conf
A low-order model of biological neural networks for hierarchical or temporal pattern clustering, detection and recognition.
IJCNN
James Ting-Ho Lo
2010 J jnl
Convexification for data fitting.
J. Glob. Optim.
James Ting-Ho Lo
2010 J jnl
Convexification for data fitting.
J. Glob. Optim.
James Ting-Ho Lo
2010 Misc conf
Unsupervised Hebbian learning by recurrent multilayer neural networks for temporal hierarchical pattern recognition.
CISS
James Ting-Ho Lo
2009 J jnl
Adaptive Capability of Recurrent Neural Networks with Fixed Weights for Series-Parallel System Identification.
Neural Comput.
James Ting-Ho Lo
2008 B conf
Probabilistic associative memories.
IJCNN
James Ting-Ho Lo
1997 — conf
Overcoming recurrent neural networks' compactness limitation for neurofiltering.
ICNN
James Ting-Ho Lo, Lei Yu
1997 — conf
Robust adaptive identification of dynamic systems by neural networks.
ICNN
James Ting-Ho Lo
1997 — conf
Robust adaptive neurofilters with or without online weight adjustment.
ICNN
James Ting-Ho Lo
1996 — conf
Adaptive system identification by nonadaptively trained neural networks.
ICNN
James Ting-Ho Lo
1994 J jnl
Synthetic approach to optimal filtering.
IEEE Trans. Neural Networks
James Ting-Ho Lo
1993 — conf
Recursive direction finding in the presence of sensor array uncertainties.
ICASSP (4)
Joseph H. Clements III, James Ting-Ho Lo
1992 J jnl
Observability conditions for multiple signal direction finding and array sensor localization.
IEEE Trans. Signal Process.
James Ting-Ho Lo, Stanley Lawrence Marple Jr.
1991 Misc conf
Backestimation for training multilayer perceptrons.
ICASSP
James Ting-Ho Lo
1990 Misc conf
Array sensor localization and calibration by cyclic regression.
ICASSP
James Ting-Ho Lo
1988 Misc conf
New maximum likelihood approach to multiple signal estimation.
ICASSP
James Ting-Ho Lo
1987 Misc conf
Eigenstructure methods for array sensor localization.
ICASSP
James Ting-Ho Lo, Stanley Lawrence Marple Jr.
1987 J jnl
Optimal functional expansion for estimation from counting observations.
IEEE Trans. Inf. Theory
James Ting-Ho Lo, Sze-Kui Ng
1979 J jnl
Exponential Fourier densities and optimal estimation for axial processes.
IEEE Trans. Inf. Theory
James Ting-Ho Lo, Linda R. Eshleman
1977 J jnl
Exponential Fourier densities and optimal estimation and detection on the circle.
IEEE Trans. Inf. Theory
James Ting-Ho Lo
1977 J jnl
Exponential Fourier densities on S2 and optimal estimation and detection for directional processes.
IEEE Trans. Inf. Theory
James Ting-Ho Lo, Linda R. Eshleman
1975 J jnl
A general bayes rule and its application to nonlinear estimation.
Inf. Sci.
James Ting-Ho Lo
1975 J jnl
Representation of Continuous Curves on the 3-Dimensional Rotation Group.
Math. Syst. Theory
James Ting-Ho Lo
1975 J jnl
Signal detection for bilinear systems.
Inf. Sci.
James Ting-Ho Lo
1974 J jnl
On optimal nonlinear estimation -- Part II: Discrete observation.
Inf. Sci.
James Ting-Ho Lo
1974 J jnl
Signal Detection of Rotational Processes and Frequency Demodulation
Inf. Control.
James Ting-Ho Lo
1973 J jnl
On optimal nonlinear estimation part I: Continuous observation.
Inf. Sci.
James Ting-Ho Lo
1972 J jnl
Finite-dimensional sensor orbits and optimal nonlinear filtering.
IEEE Trans. Inf. Theory
James Ting-Ho Lo